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import gradio as gr
import fastai
from fastai.vision.all import *
def label_func(x):
if x.name[0] == 'm':
return "Mustang"
elif x.name[1] == "a":
return "Camaro"
elif x.name[1] == "h":
return "Challenger"
learn = load_learner('export-2.pkl')
labels = learn.dls.vocab
def predict(img):
img = PILImage.create(img)
pred,pred_idx,probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
gr.Interface(fn=predict, inputs=gr.Image(type='pil'), outputs=gr.Label(num_top_classes=3)).launch(share=True)
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